Lead Generative AI Developer

** About the Role*
* We are looking for a  
** Lead Generative AI Developer
** to join our COO Technology Division in New York. In this high-impact role, you will architect, develop, and operationalize cutting-edge Generative AI and Large Language Model (LLM) solutions that directly transform how Citi's operational teams work. You will collaborate with cross-functional stakeholders - including operations leads, data engineers, product managers, and enterprise architects to deliver enterprise-grade AI capabilities at scale.

This is a hands-on engineering role for a builder who thrives at the intersection of applied AI research and production software engineering.

** Key Responsibilities*
* +  
** Design & Build GenAI Solutions:
** Architect and implement end-to-end Generative AI pipelines including LLM integrations, Retrieval-Augmented Generation (RAG) systems, autonomous AI agents, and prompt engineering frameworks.

+  
** Python Development:
** Develop robust, scalable, and production-ready Python services and APIs that power AI-driven features across COO platforms.

+  
** Model Integration & Fine-tuning:
** Evaluate, integrate, and fine-tune LLMs (e.g., GPT-5, Claude, Mistral) and embedding models for domain-specific financial use cases.

+  
** MLOps & Deployment:
** Build and maintain ML/GenAI deployment pipelines using modern MLOps practices, ensuring reliability, observability, and governance.

+  
** Agentic Workflows:
** Design and implement multi-agent orchestration frameworks (e.g., Lang Graph, Google ADK) for complex, multi-step operational workflows.

+  
** Enterprise AI Governance:
** Collaborate with Citi's AI Risk and Compliance teams to ensure all AI solutions align with regulatory requirements, responsible AI frameworks, and data privacy standards.

+  
** Data Engineering:
** Design and optimize data pipelines feeding AI systems, working with vector databases (e.g., Pinecone, Weaviate, pgvector) and enterprise data platforms.

+  
** Technical Leadership:
** Mentor junior developers, lead code reviews, and contribute to GenAI standards and best practices across the COO Technology organization.

+  
** Stakeholder

Collaboration:

** Translate complex business requirements from COO operations stakeholders into technical AI solutions, providing clear communication of trade-offs and timelines.

** Required Qualifications*
* +  
*
* Experience:

** 10+ years of professional software engineering experience, with at least  
** 2+ years focused on Generative AI / LLM application development** .

+  
** Python:
** Expert-level Python proficiency - including async programming, API development (FastAPI, Flask), and software design patterns.

+  
** GenAI & LLM Stack:*
* + Deep hands-on experience with LLM frameworks:  
** Lang Chain, Lang Graph, Llama Index etc*
* + Hands on experience with  
** Google Cloud AI Platform*
* + Proven experience with  
** RAG architectures** , embedding pipelines, and vector search

+ Strong understanding of  
** prompt engineering, few-shot learning, and chain-of-thought
** techniques

+ Experience integrating with LLM APIs:  
** OpenAI, Azure OpenAI, Anthropic, AWS Bedrock, or Google Vertex AI*
* +  
** Machine Learning:
** Solid grounding in ML fundamentals; familiarity with model evaluation, fine-tuning (LoRA, PEFT), and inference optimization.

+  
** Cloud Platforms:
** Hands-on experience with at least one major cloud provider
- ** AWS, Azure, or GCP**  - particularly managed AI/ML services.

+  
** Data & Databases:
** Proficiency with SQL, No

SQL, and  
** vector databases**  (Pinecone, Weaviate, Chroma, pgvector).

+  
** Software Engineering Practices:
** Strong understanding of CI/CD pipelines, containerization (
** Docker, Kubernetes** ), version control (Git), and automated testing.

+  
** Financial Services Acumen (Preferred):
** Prior experience in banking, fintech, or a regulated industry is a strong plus.

** Preferred Qualifications*
* +

Experience with  
** multi-agent orchestration
** frameworks (MS Agent Framework, ADK, Strands, Lang Graph)

+ Familiarity with  
** MLflow, Weights & Biases, or similar
** experiment tracking and model management tools

+ Knowledge of  
** responsible AI practices** : bias detection, explainability, hallucination mitigation

+ Exposure to  
** Kafka, Spark, or Airflow
** for data pipeline engineering

+ Experience working in an Agile/SAFe delivery environment

+ Advanced degree (M.S.) in Computer Science, AI/ML, or a related discipline - or equivalent demonstrated experience

** Technical Stack (Working Knowledge Expected)*
* ** Languages** :
Python (expert), SQL, Bash

** GenAI Frameworks** :
Lang Chain, Llama Index, Lang Graph, Semantic Kernel

** LLM Providers** :
OpenAI / Azure OpenAI, Anthropic, AWS Bedrock, Google Vertex AI

** Vector Databases** :
Pinecone, Weaviate, pgvector, Chroma

** Cloud** : AWS / Azure / GCP

** MLOps** : MLflow, Docker, Kubernetes, Git Hub Actions

** Data Engineering** :
Spark, Airflow, Kafka

** Databases** :
PostgreSQL, MongoDB, Redis

*
* Education:

*
* + Bachelor's degree/University degree or equivalent…